Evidence map›Paper›PMID 32764205›Full record

ArticleClinical and translational gastroenterology2020

Oncogenic Features in Histologically Normal Mucosa: Novel Insights Into Field Effect From a Mega-Analysis of Colorectal Transcriptomes.

Christopher H Dampier, Matthew Devall, Lucas T Jennelle, Virginia Díez-Obrero, Sarah J Plummer, Victor Moreno, Graham Casey

Open access · goldAbstract read
In one paragraph

Article in Clinical and translational gastroenterology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.7field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 17 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Christopher H DampierDepartment of Surgery, University of Virginia, Charlottesville, Virginia, USA.
Matthew DevallCenter for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA.
Lucas T JennelleCenter for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA.
Virginia Díez-ObreroDepartment of Surgery, University of Virginia, Charlottesville, Virginia, USA.
Sarah J PlummerCenter for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA.
Victor MorenoDepartment of Surgery, University of Virginia, Charlottesville, Virginia, USA.
Graham CaseyCenter for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA.
University of Virginia · USCentro de Investigación Biomédica en Red de Epidemiología y Salud Pública · ESInstitut d'Investigació Biomédica de Bellvitge · ES

Funding

Inherited colorectal cancer risk variants: from association to biologyR01CA143237 · NCI · UNIVERSITY OF VIRGINIA · PI CASEY, GRAHAM · 2010 to 2020
$8.4M
Postdoctoral Training Grant for MDs in Surgical Oncology ResearchT32CA163177 · NCI · UNIVERSITY OF VIRGINIA · PI Craig Lee Slingluff, Allan Tsung · 2011 to 2026
$4.6M
NCI NIH HHS R01 CA143237NCI NIH HHS T32 CA163177
6 · The paper itself

Abstract

introductionColorectal cancer is a common malignancy that can be cured when detected early, but recurrence among survivors is a persistent risk. A field effect of cancer in the colon has been reported and could have implications for surveillance, but studies to date have been limited. A joint analysis of pooled transcriptomic data from all available bulk RNA-sequencing data sets of healthy, histologically normal tumor-adjacent, and tumor tissues was performed to provide an unbiased assessment of field effect.

methodsA novel bulk RNA-sequencing data set from biopsies of nondiseased colon from screening colonoscopy along with published data sets from the Genomic Data Commons and Sequence Read Archive were considered for inclusion. Analyses were limited to samples with a quantified read depth of at least 10 million reads. Transcript abundance was estimated with Salmon, and downstream analysis was performed in R.

resultsA total of 1,139 samples were analyzed in 3 cohorts. The primary cohort consisted of 834 independent samples from 8 independent data sets, including 462 healthy, 61 tumor-adjacent, and 311 tumor samples. Tumor-adjacent gene expression was found to represent an intermediate state between healthy and tumor expression. Among differentially expressed genes in tumor-adjacent samples, 1,143 were expressed in patterns similar to tumor samples, and these genes were enriched for cancer-associated pathways. DISCUSSION: Novel insights into the field effect in colorectal cancer were generated in this mega-analysis of the colorectal transcriptome. Oncogenic features that might help explain metachronous lesions in cancer survivors and could be used for surveillance and risk stratification were identified.

Indexed as

Biomarkers, TumorBiopsyCarcinogenesisCohort StudiesColonColonoscopyColorectal NeoplasmsComputational BiologyDatasets as TopicGene Expression Regulation, NeoplasticHumansIntestinal MucosaMass ScreeningRNA-SeqTranscriptomeBiomarkers, Tumor

Identifiers

PMID32764205
PMCPMC7386360
OpenAlexW3043855777

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.